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We examined the correspondence between intrinsic fMRI and EEG network activity at rest in order to characterize brain networks both spatially (with fMRI) and spectrally (with EEG). ... Brain networks were separately identified within the concurrently recorded fMRI and EEG at the aggregate group level with group independent component analysis and the association between spatial fMRI and ... This research was supported by National Institute of Heath grants NIBIB 1R01EB006841 and NCRR 5P20RR021938. ...doi:10.1016/j.neuroimage.2012.12.024 pmid:23266744 pmcid:PMC3568990 fatcat:etg5dqeb2vfpnm7xuhpfyxvkfu
EEG-fMRI F-map of each δ 4 model showed strong engagement of insula, cuneus, precuneus, basal ganglia, sensory-motor, motor and dorsal part of fronto-parietal control (FPCN) networks with fast HRF peak ... We tested four EEG-fMRI fusion models utilizing EEG power spectra fluctuations (i.e., absolute spectral model - ASM; relative spectral model - RSM; absolute spatiospectral model - ASSM; and relative spatiospectral ... ACKNOWLEDGMENTS All EEG-fMRI measurements were performed at the 1 st Department of Neurology, St. Anne's University Hospital Brno, Czech Republic. Authors thanks to Drs. R. Mareček and M. ...doi:10.3389/fneur.2021.644874 pmid:33981283 pmcid:PMC8107237 fatcat:hm7pmuaorfbknbhclqpk7zvsgi
The resulting EEG-fMRI networks capture a broader range of brain dynamics compared to EEG or fMRI alone, and can serve as a reference for studies integrating MEG and fMRI. ... The following chapter surveys the physiological differences between EEG and fMRI recordings and the implications and results of their integration. ... Fluctuations in ERP and fMRI maps across subjects may be directly compared with results from MEG, which can further improve the ability to spatiotemporally characterize brain activity (Plis et al. 2010 ...doi:10.1007/978-3-642-33045-2_9 fatcat:ovf2zk5g75h7haqh23ysz26zr4